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Heart signal processing Using wavelet Analysis and Deep Learning Algorithms Based on Artificial Intelligence

Heart Signal Processing Using Wavelet Analysis and Deep Lear...

引用

International conference on applications in Electronics Pervading Industry, Environment and Society, APPLEPIES 2024

作者： Zilaie, Morteza Mohammadkhani, Zohreh Asrari, Keyvan Azimi Talebiyan, Seyed Reza Islamic Azad University Science and Research Branch Khorasan Razavi Mashhad Iran The University of Pavia Pavia Italy Imam Reza International University Khorasan Razavi Mashhad Iran

ISBN: (纸本)9783031840999

The electrocardiogram signal of the heart is used to monitor the health status and function of the human heart and to a doctor in diagnosing the type of disease. For this purpose, first, the scalogram of the different heart failures produces different types of this signal. In this research, the cardiac signals of the patients are analyzed by an artificial intelligence neural network, and the type of the person’s disease is diagnosed. The artificial intelligence in question can be learned and can be used as an assistant ECG signal is calculated using continuous wavelet transform and then it is subjected to learning and evaluation using a deep convolutional neural network. In the architecture of artificial intelligence, two well-known neural networks GoogLeNet and SqueezeNet are used, which have been sufficiently trained in similar applications such as image processing and machine vision. In the end, the type of heart failure is diagnosed and classified. The cardiac signals of the patients used in the simulation were extracted from the PhysioNet medical engineering standard dataset of MIT University. In the end, the simulation results of the research are given. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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A Speech Enhancement Algorithm Combining wavelet Transform and Adaptive Filters 6

A Speech Enhancement Algorithm Combining Wavelet Transform a...

引用

6th IEEE International conference on image processing, applications and Systems, IPAS 2025

作者： Shrestha, Aayam Ghorshi, Seyed Joorabchi, Marjan Panahi, Issa Firouzeh, Fereshteh Fakhar The University of Texas at Tyler Department of Electrical and Computer Engineering TX United States Sharif University of Technology School of Science and Engineering Iran The University of Texas at Dallas Department of Electrical and Computer Engineering TX United States

ISBN: (纸本)9798331506520

Noise as an unwanted interference can significantly degrade speech signals, especially those recorded by many microphones. This interference is modeled as additive noise that originates from a range of sources including White Gaussian Noise (WGN), babble, crowd, large city, and traffic noises. These disturbances can alter the characteristics of speech signals reducing both their quality and intelligibility. This paper introduces a novel approach designed to reduce noise and enhance the quality and intelligibility of speech signals. The proposed method combines wavelet Transform with Adaptive Filters, specifically the Wiener filter and RLS filter. The evaluation process involves testing noisy speech signals under realistic conditions with different signal-to-noise ratios (SNRs) and different types of additive noise. The objective measure is used for evaluation, including the perceptual evaluation of speech quality (PESQ). Results show that combining Wiener or RLS filtering with wavelet Transform significantly improves noise reduction, outperforming the use of wavelet Transform alone. © 2025 IEEE.

关键词： Adaptive filtering

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3rd International conference on Machine Vision and Augmented Intelligence, MAI 2023

3rd International Conference on Machine Vision and Augmented...

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3rd International conference on Machine Vision and Augmented Intelligence, MAI 2023

ISBN: (纸本)9789819743582

The proceedings contain 76 papers. The special focus in this conference is on Machine Vision and Augmented Intelligence. The topics include: Survey on Robustness of Deep Learning Techniques on Adversarial Attacks in WBAN;synergizing Collaborative and Content-Based Filtering for Enhanced Movie Recommendations;exploring Transformer-Based Approaches for Hyperspectral image Classification: A Comparative Analysis;deep Learning for Cognitive Task and Seizure Classification with Hilbert–Huang Transform and Variational Mode Decomposition;tracking of Ship and Plane in Satellite Videos Using a Convolutional Regression Network with Deep Features;Tumor Detection and Analysis from Brain MRI images Using Deep Learning;software Maintenance Prediction Using Stack Ensemble Deep Learning Algorithms;resource Allocation in 6G Network for High-Speed Train Using D2D Outband Communication;controlling the Band-to-Band Tunneling Effect in Charge Plasma Based Dopingless Transistor;Comparison of Different CIC Filter Architectures on the Basis of a Novel Parameter Called Noise Factor for Sigma-Delta Based ADCs;the Scientific Analysis on Effective Yoga Posture Recognition Techniques;impact of Gamma Rays on Emerging Devices for Photonic applications;shaft Rotation Monitoring Using Radar signal processing and wavelet Transform;gysel Power Divider Miniaturization Using an Inter-Digital Capacitor-Based Slow-Wave Structure;noise Estimation and Removal in Fundus images Using Pyramid Real image Denoising Network;evaluation of Hybrid Encryption Method to Secure Healthcare Data;multimodal Face Recognition System Using Hybrid Deep Learning Feature;Classification of Copy and Move image by Using HELM-FSK Method: An Efficient Approach;analysis of Energy Efficient Smart Home Based on IoT System;role of Explainable Artificial Intelligence Approaches in Cybersecurity.

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An Improved Digital signal processing for signal Enhancement and Interference Mitigation

An Improved Digital Signal Processing for Signal Enhancement...

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Automation and Computation (AUTOCOM), International conference on

作者： Intekhab Alam Paramjit Baxi Barnali Sahoo Mohan Garg Roopashree R Thaj Mary Delsy T Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Sciences Chemistry and Biochemistry JAIN (Deemed to be University) Bangalore Karnataka India Department of Electronics and Communication Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Digital signal processing has become a fundamental tool in signal processing applications, such as speech and image processing, due to its ability to manipulate and examine signals in a digital form skillfully. A primary challenge in signal processing involves the presence of unwanted noise and interference, which can negatively impact the precision and quality of the processed signal. The proposed advanced DSP approach aims to improve signal enhancement and interference mitigation techniques using sophisticated algorithms and methods. The proposed state-of-the-art DSP approach includes noise reduction algorithms, such as adaptive filtering and spectral subtraction, to eliminate unwanted noise from the signal. Additionally, cutting-edge signal processing techniques, such as wavelet transforms and time-frequency analysis, are used for signal enhancement and demising. The proposed approach employs adaptive equalization techniques to mitigate interference from other signals and substantially improve the overall signal quality. The enhanced DSP approach is evaluated through simulation and real-world experiments, demonstrating its effectiveness in improving signal quality and reducing interference considerably. The proposed approach has the potential to significantly improve the accuracy and reliability of various signal processing applications considerably, making it a valuable tool in fields such as telecommunications, audio and video processing, and medical signal analysis.

关键词： Wireless communication wavelet transforms Time-frequency analysis Accuracy Prevention and mitigation signal processing algorithms Interference Digital signal processing wavelet analysis Telecommunications

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A Speech Enhancement Algorithm Combining wavelet Transform and Adaptive Filters

A Speech Enhancement Algorithm Combining Wavelet Transform a...

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International image processing, applications and Systems conference (IPAS)

作者： Aayam Shrestha Seyed Ghorshi Marjan Joorabchi Issa Panahi Fereshteh Fakhar Firouzeh Department of Electrical and Computer Engineering The University of Texas at Tyler Texas USA School of Science and Engineering Sharif University of Technology Iran Department of Electrical and Computer Engineering The University of Texas at Dallas Texas USA

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

关键词： wavelet transforms Additive noise Wiener filters Filtering Noise Urban areas Adaptive filters Interference Speech enhancement wavelet analysis

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wavelet-based contrast computation and application to digital image watermarking

Wavelet-based contrast computation and application to digita...

引用

conference on wavelet applications in signal and image processing viii

作者： Vandergheynst, P Kutter, M Winkler, S Swiss Fed Inst Technol Signal Proc Lab CH-1015 Lausanne Switzerland

ISBN: (纸本)0819437646

We introduce an isotropic measure of local contrast for natural images that is based on analytic filters and present the design of directional wavelet frames suitable for its computation. We show how this contrast measure can be used within a masking model to facilitate the insertion of a watermark in an image while minimizing visual distortion.

关键词： Digital watermarking wavelets Visual process modeling Transducers image filtering Visualization Bandpass filters Curium image quality Optical filters

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image denoising using orthonormal finite ridgelet transform

Image denoising using orthonormal finite ridgelet transform

引用

conference on wavelet applications in signal and image processing viii

作者： Do, MN Vetterli, M Ecole Polytech Fed Lausanne LCAV CH-1015 Lausanne Switzerland

ISBN: (纸本)0819437646

This paper addresses the image denoising problem using a newly proposed digital image transform: the finite ridgelet transform (FRIT). The transform is invertible, non-redundant and achieved via fast algorithms. Furthermore this transform can be designed to be orthonormal thus indicating its potential in many other image processing applications. We then propose various improvements on the initial design of the FRIT in order to make it to have better energy compaction and to reduce the border effect. Experimental results show that the new transform outperforms wavelets in denoising images with linear discontinuities.

关键词： wavelets Discrete wavelet transforms Denoising Radon transform image denoising wavelet transforms Fourier transforms Radon Digital imaging image processing

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wavelet denoising by MSFI and NSFI

Wavelet denoising by MSFI and NSFI

引用

conference on wavelet applications in signal and image processing viii

作者： Lin, EB Univ Toledo Dept Math Toledo OH 43606 USA

ISBN: (纸本)0819437646

image denoising in wavelet transform domain using thresholding is one of the most effective techniques of image enhancement. Even though the thresholding on the wavelet transform domain generally works well, one can still visually note the remaining noise in the resulting image, especially in the non-edge areas. In this paper, we use Multi-scaling Function Interpolation and Nonseparable Scaling Function Interpolation to smooth the noise image. Several simulation results will be presented and comparisons between MSFI and NSFI methods will be shown.

关键词： wavelet denoising multi-scaling function interpolation nonseparable scaling function interpolation

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Compactly supported wavelets and representations of the Cuntz relations, II

Compactly supported wavelets and representations of the Cunt...

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conference on wavelet applications in signal and image processing viii

作者： Jorgensen, PET Univ Iowa Dept Math Iowa City IA 52242 USA

ISBN: (纸本)0819437646

We show that compactly supported wavelets in L-2 (R) of scale N may be effectively parameterized with a finite set of spin vectors in C-N, and conversely that every set of spin vectors corresponds to a wavelet. The characterization is given in terms of irreducible representations of orthogonality relations defined from multiresolution wavelet filters.

关键词： wavelet Cuntz algebra representation orthogonal expansion quadrature mirror filter isometry in Hilbert space

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Multiscale edge representation applied to image fusion

Multiscale edge representation applied to image fusion

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conference on wavelet applications in signal and image processing viii

作者： Scheunders, P Univ Antwerp Vis Lab B-2020 Antwerp Belgium

ISBN: (纸本)0819437646

In this paper the fusion of multimodal images into one greylevel image is aimed at. A multiresolution technique, based on the wavelet multiscale edge representation is applied. The fusion consists of retaining only the modulus maxima of the wavelet coefficients from the different bands and combining them. After reconstruction, a synthetic image is obtained that contains the edge information from all bands simultaneously. Noise reduction is applied by removing the noise-related modulus maxima. In several experiments on test images and multispectral satellite images, we demonstrate that the proposed technique outperforms mapping techniques, as PCA and SOM and other wavelet-based fusion techniques.

关键词： multiscale edge representation wavelet-based image fusion multispectral image merging

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